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We examine how the return predictability of deep learning models varies with stocks’ vulnerability to investors’ behavioral biases. Using an extensive list of anomaly variables, we find that the long-short strategy based on deep learning signals generates greater returns for stocks more...
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We find that investors' future trading decisions are driven by the patterns of their social neighborhood and the trading activity therein. Moreover, we provide evidence that investors weigh their social connections differently in terms of information transfer. Methodologically, we tackle the...
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Predictive AI is increasingly used to guide decisions on agents. I show that even a bias-neutral predictive AI can … potentially amplify exogenous (human) bias in settings where the predictive AI represents a cost-adjusted precision gain to … belief updating, expected victims of bias become less likely to be saved by randomness under more precise predictions. An …
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